o ?Biu` @s\dZddlZddlZddlZddlmZm Z GdddeZ GdddeZ Gdd d eZ Gd d d eZ Gd d d eZGdddeZGdddeZGdddeZGdddeZd6ddZd6ddZd7ddZd8dd Zd9d"d#Zd9d$d%Z d:d&ejed'efd(d)Zd6d*d+Zd9d,d-Z ! d9d.ejd/ejd0ejd1ejd2ed3ef d4d5Z dS);zi .. module:: volume :synopsis: Volume Indicators. .. moduleauthor:: Dario Lopez Padial (Bukosabino) N)IndicatorMixin_emac @sReZdZdZ ddejdejdejdejdef dd Zd d Zd ejfd dZ dS)AccDistIndexIndicatoraAccumulation/Distribution Index (ADI) Acting as leading indicator of price movements. https://school.stockcharts.com/doku.php?id=technical_indicators:accumulation_distribution_line Args: high(pandas.Series): dataset 'High' column. low(pandas.Series): dataset 'Low' column. close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. fillna(bool): if True, fill nan values. FhighlowclosevolumefillnacC*||_||_||_||_||_|dSN)_high_low_close_volume_fillna_run)selfrrrrr rI/var/www/html/Trade-python/venv/lib/python3.10/site-packages/ta/volume.py__init__  zAccDistIndexIndicator.__init__cCsF|j|j|j|j|j|j}|d}||j}||_dSN)rr r r rcumsum_adi)rclvadirrrr/s    zAccDistIndexIndicator._runreturncC|j|jdd}tj|ddS)zrAccumulation/Distribution Index (ADI) Returns: pandas.Series: New feature generated. rvaluername) _check_fillnarpdSeries)rrrrracc_dist_index7z$AccDistIndexIndicator.acc_dist_indexNF) __name__ __module__ __qualname____doc__r$r%boolrrr&rrrrrs  rc@DeZdZdZddejdejdefddZdd Zd ejfd d Z d S)OnBalanceVolumeIndicatora_On-balance volume (OBV) It relates price and volume in the stock market. OBV is based on a cumulative total volume. https://en.wikipedia.org/wiki/On-balance_volume Args: close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. fillna(bool): if True, fill nan values. Frrr cC||_||_||_|dSr rrrrrrrr rrrrO z!OnBalanceVolumeIndicator.__init__cCs>t|j|jdk|j |j}tj||jjd|_ dS)N)index) npwherershiftrr$r%r5r_obvrobvrrrrUs"zOnBalanceVolumeIndicator._runrcCr)zdOn-balance volume (OBV) Returns: pandas.Series: New feature generated. rrr;r!)r#r9r$r%r:rrron_balance_volumeYr'z*OnBalanceVolumeIndicator.on_balance_volumeNr() r)r*r+r,r$r%r-rrr<rrrrr/As  r/c @XeZdZdZ  ddejdejdejdejded ef d d Zd d Z dejfddZ dS)ChaikinMoneyFlowIndicatoraChaikin Money Flow (CMF) It measures the amount of Money Flow Volume over a specific period. http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:chaikin_money_flow_cmf Args: high(pandas.Series): dataset 'High' column. low(pandas.Series): dataset 'Low' column. close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. window(int): n period. fillna(bool): if True, fill nan values. Frrrrwindowr cC0||_||_||_||_||_||_|dSr r r rr_windowrrrrrrrr@r rrrrs  z"ChaikinMoneyFlowIndicator.__init__cCsx|j|j|j|j|j|j}|d}||j9}|jr!dn|j}|j|j|d|jj|j|d|_ dS)Nrr min_periods) rr r r rrrCrollingsum_cmf)rmfvrGrrrrs   zChaikinMoneyFlowIndicator._runrcCr)zeChaikin Money Flow (CMF) Returns: pandas.Series: New feature generated. rrcmfr!)r#rJr$r%)rrLrrrchaikin_money_flowr'z,ChaikinMoneyFlowIndicator.chaikin_money_flowNr?F) r)r*r+r,r$r%intr-rrrMrrrrr>cs&  r>c @sLeZdZdZ  ddejdejdedefdd Zd d Z d ejfd dZ dS)ForceIndexIndicatoraForce Index (FI) It illustrates how strong the actual buying or selling pressure is. High positive values mean there is a strong rising trend, and low values signify a strong downward trend. http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:force_index Args: close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. window(int): n period. fillna(bool): if True, fill nan values. Frrr@r cCs$||_||_||_||_|dSr )rrrCrr)rrrr@r rrrrs  zForceIndexIndicator.__init__cCs0|j|jd|j}t||j|jd|_dS)Nr4)r )rr8rrrCr_fir fi_seriesrrrrszForceIndexIndicator._runrcC&|j|jdd}tj|d|jdS)z]Force Index (FI) Returns: pandas.Series: New feature generated. rrfi_r!)r#rRr$r%rCrSrrr force_indexzForceIndexIndicator.force_indexNrQF) r)r*r+r,r$r%rOr-rrrWrrrrrPs  rPc @sbeZdZdZ  ddejdejdejdedef d d Zd d Z d ejfddZ d ejfddZ dS)EaseOfMovementIndicatoraEase of movement (EoM, EMV) It relate an asset's price change to its volume and is particularly useful for assessing the strength of a trend. https://en.wikipedia.org/wiki/Ease_of_movement Args: high(pandas.Series): dataset 'High' column. low(pandas.Series): dataset 'Low' column. volume(pandas.Series): dataset 'Volume' column. window(int): n period. fillna(bool): if True, fill nan values. Frrrr@r cCr r )r r rrCrr)rrrrr@r rrrrrz EaseOfMovementIndicator.__init__cCsB|jd|jd|j|jd|j|_|jd9_dS)Nr4i)r diffr r_emv)rrrrrs zEaseOfMovementIndicator._runrcCrU)zhEase of movement (EoM, EMV) Returns: pandas.Series: New feature generated. rreom_r!)r#r^r$r%rC)remvrrrease_of_movementrXz(EaseOfMovementIndicator.ease_of_movementcCsJ|jrdn|j}|jj|j|d}|j|dd}tj|d|jdS)zoSignal Ease of movement (EoM, EMV) Returns: pandas.Series: New feature generated. rrFrsma_eom_r!)rrCr^rHmeanr#r$r%)rrGr`rrrsma_ease_of_movementsz,EaseOfMovementIndicator.sma_ease_of_movementNr[F) r)r*r+r,r$r%rOr-rrrardrrrrrZs$  rZc @sXeZdZdZ   ddejdejdedeje def d d Z d d Z d ejfddZ dS)VolumePriceTrendIndicatoraVolume-price trend (VPT) Is based on a running cumulative volume that adds or substracts a multiple of the percentage change in share price trend and current volume, depending upon the investment's upward or downward movements. https://en.wikipedia.org/wiki/Volume%E2%80%93price_trend Args: close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. fillna(bool)=False: if True, fill nan values. DO NOT RECCOMEND to set it True. smoothing_factor(int)=None: will smooth default VPT implementation with SMA. dropnans(bool)=False: drop nans after indicator calculated. FNrrr smoothing_factordropnanscCr r )rrr_smoothing_factor _dropnansr)rrrr rgrhrrrrrz"VolumePriceTrendIndicator.__init__cCs^|j|j|_|jr"|jrdn|j}|jj|j|d|_|j r-|j |_dSdS)NrrF) r pct_changerr_vptrirrHrcrjdropna)rrGrrrr!szVolumePriceTrendIndicator._runrcCr)zeVolume-price trend (VPT) Returns: pandas.Series: New feature generated. rrvptr!)r#rlr$r%)rrnrrrvolume_price_trend+r'z,VolumePriceTrendIndicator.volume_price_trendFNF) r)r*r+r,r$r%r-tpOptionalrOrrrorrrrrfs$  rfc@r.)NegativeVolumeIndexIndicatora9Negative Volume Index (NVI) http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:negative_volume_inde Args: close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. fillna(bool): if True, fill nan values with 1000. Frrr cCr0r r1r2rrrr@r3z%NegativeVolumeIndexIndicator.__init__cCs|j}|jd|jk}tjtj|jjddd|_ d|j j d<t dt |j D]'}|j |rD|j j |dd|j ||j j |<q)|j j |d|j j |<q)dS)Nr4float64nvi)datar5dtyper"rg?) rrkrr8r$r%r6nanr5_nviilocrangelen)r price_change vol_decreaseirrrrFs   (z!NegativeVolumeIndexIndicator._runrcCr)zhNegative Volume Index (NVI) Returns: pandas.Series: New feature generated. rxrrur!)r#rzr$r%)rrurrrnegative_volume_indexSsz2NegativeVolumeIndexIndicator.negative_volume_indexNr() r)r*r+r,r$r%r-rrrrrrrrs5s   rsc @r=) MFIIndicatoraMoney Flow Index (MFI) Uses both price and volume to measure buying and selling pressure. It is positive when the typical price rises (buying pressure) and negative when the typical price declines (selling pressure). A ratio of positive and negative money flow is then plugged into an RSI formula to create an oscillator that moves between zero and one hundred. http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:money_flow_index_mfi Args: high(pandas.Series): dataset 'High' column. low(pandas.Series): dataset 'Low' column. close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. window(int): n period. fillna(bool): if True, fill nan values. r[Frrrrr@r cCrAr rBrDrrrrrrEzMFIIndicator.__init__c Cs|j|j|jd}t||dkdt||dkdd}||j|}|jr-dn|j}|j |j|dj dddd }t |j |j|dj d ddd }||}d d d||_ dS) N@r4rrFcSstt|dk|dSrr6rIr7xrrrz#MFIIndicator._run..T)rawcSstt|dk|dSrrrrrrrrd) r r rr6r7r8rrrCrHapplyabs_mfi)r typical_priceup_downmfrrG n_positive_mf n_negative_mfmfirrrrs$  zMFIIndicator._runrcCrU)zcMoney Flow Index (MFI) Returns: pandas.Series: New feature generated. 2rmfi_r!)r#rr$r%rC)rrrrrmoney_flow_indexrXzMFIIndicator.money_flow_indexNre) r)r*r+r,r$r%rOr-rrrrrrrr^s& rc @r=)VolumeWeightedAveragePriceVolume Weighted Average Price (VWAP) VWAP equals the dollar value of all trading periods divided by the total trading volume for the current day. The calculation starts when trading opens and ends when it closes. Because it is good for the current trading day only, intraday periods and data are used in the calculation. https://school.stockcharts.com/doku.php?id=technical_indicators:vwap_intraday Args: high(pandas.Series): dataset 'High' column. low(pandas.Series): dataset 'Low' column. close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. window(int): n period. fillna(bool): if True, fill nan values. Returns: pandas.Series: New feature generated. r[Frrrrr@r cCrAr rBrDrrrrrEz#VolumeWeightedAveragePrice.__init__cCsh|j|j|jd}||j}|jrdn|j}|j|j|d}|jj|j|d}|||_dS)NrrrF) r r rrrrCrHrIvwap)rrtypical_price_volumerGtotal_pv total_volumerrrrs zVolumeWeightedAveragePrice._runrcCs"||j}tj|d|jdS)zqVolume Weighted Average Price (VWAP) Returns: pandas.Series: New feature generated. vwap_r!)r#rr$r%rC)rrrrrvolume_weighted_average_prices z8VolumeWeightedAveragePrice.volume_weighted_average_priceNre) r)r*r+r,r$r%rOr-rrrrrrrrs& rFcCt|||||dS)aAccumulation/Distribution Index (ADI) Acting as leading indicator of price movements. https://en.wikipedia.org/wiki/Accumulation/distribution_index Args: high(pandas.Series): dataset 'High' column. low(pandas.Series): dataset 'Low' column. close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. fillna(bool): if True, fill nan values. Returns: pandas.Series: New feature generated. rrrrr )rr&rrrrr&s  r&cCt|||dS)aOn-balance volume (OBV) It relates price and volume in the stock market. OBV is based on a cumulative total volume. https://en.wikipedia.org/wiki/On-balance_volume Args: close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. fillna(bool): if True, fill nan values. Returns: pandas.Series: New feature generated. rrr )r/r<rrrrr<s r<r?cCst||||||dS)a8Chaikin Money Flow (CMF) It measures the amount of Money Flow Volume over a specific period. http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:chaikin_money_flow_cmf Args: high(pandas.Series): dataset 'High' column. low(pandas.Series): dataset 'Low' column. close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. window(int): n period. fillna(bool): if True, fill nan values. Returns: pandas.Series: New feature generated. rrrrr@r )r>rMrrrrrMs  rMrQcCst||||dS)a1Force Index (FI) It illustrates how strong the actual buying or selling pressure is. High positive values mean there is a strong rising trend, and low values signify a strong downward trend. http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:force_index Args: close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. window(int): n period. fillna(bool): if True, fill nan values. Returns: pandas.Series: New feature generated. rrr@r )rPrWrrrrrW.s rWr[cCraEase of movement (EoM, EMV) It relate an asset's price change to its volume and is particularly useful for assessing the strength of a trend. https://en.wikipedia.org/wiki/Ease_of_movement Args: high(pandas.Series): dataset 'High' column. low(pandas.Series): dataset 'Low' column. volume(pandas.Series): dataset 'Volume' column. window(int): n period. fillna(bool): if True, fill nan values. Returns: pandas.Series: New feature generated. rrrr@r )rZrarrrrraE  racCrr)rZrdrrrrrd\rrdrgrhcCr)aVolume-price trend (VPT) Is based on a running cumulative volume that adds or substracts a multiple of the percentage change in share price trend and current volume, depending upon the investment's upward or downward movements. https://en.wikipedia.org/wiki/Volume%E2%80%93price_trend Args: close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. fillna(bool)=False: if True, fill nan values. DO NOT RECCOMEND to set it True. smoothing_factor(int)=None: will smooth default VPT implementation with SMA. dropnans(bool)=False: drop nans after indicator calculated. Returns: pandas.Series: New feature generated. rrr rgrh)rfrorrrrrossrocCr)aONegative Volume Index (NVI) http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:negative_volume_inde The Negative Volume Index (NVI) is a cumulative indicator that uses the change in volume to decide when the smart money is active. Paul Dysart first developed this indicator in the 1930s. [...] Dysart's Negative Volume Index works under the assumption that the smart money is active on days when volume decreases and the not-so-smart money is active on days when volume increases. The cumulative NVI line was unchanged when volume increased from one period to the other. In other words, nothing was done. Norman Fosback, of Stock Market Logic, adjusted the indicator by substituting the percentage price change for Net Advances. This implementation is the Fosback version. If today's volume is less than yesterday's volume then: nvi(t) = nvi(t-1) * ( 1 + (close(t) - close(t-1)) / close(t-1) ) Else nvi(t) = nvi(t-1) Please note: the "stockcharts.com" example calculation just adds the percentange change of price to previous NVI when volumes decline; other sources indicate that the same percentage of the previous NVI value should be added, which is what is implemented here. Args: close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. fillna(bool): if True, fill nan values with 1000. Returns: pandas.Series: New feature generated. See also: https://en.wikipedia.org/wiki/Negative_volume_index r)rsrrrrrrs (rcCt||||||d}|S)aTMoney Flow Index (MFI) Uses both price and volume to measure buying and selling pressure. It is positive when the typical price rises (buying pressure) and negative when the typical price declines (selling pressure). A ratio of positive and negative money flow is then plugged into an RSI formula to create an oscillator that moves between zero and one hundred. http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:money_flow_index_mfi Args: high(pandas.Series): dataset 'High' column. low(pandas.Series): dataset 'Low' column. close(pandas.Series): dataset 'Close' column. volume(pandas.Series): dataset 'Volume' column. window(int): n period. fillna(bool): if True, fill nan values. Returns: pandas.Series: New feature generated. r)rrrrrrr@r indicatorrrrrs rrrrrr@r cCr)rr)rrrrrrrs rr(rNrYrerp)!r,typingrqnumpyr6pandasr$ta.utilsrrrr/r>rPrZrfrsrrr&r<rMrWrardrrrOr-rorrr%rrrrrsV0"7+<4)J D       -"